ESTRO 2025 - Abstract Book

S4364

RTT - Treatment planning, OAR and target definitions

ESTRO 2025

Conclusion: The deep learning-based dose prediction model successfully predicted clinically acceptable dose distributions for prostate SBRT plans delivered with TrueBeam dual arc VMAT. The model's ability to generate achievable patient specific planning objectives could help standardize the planning process while maintaining high plan quality. Further prospective studies are warranted to evaluate the impact on planning efficiency and consistency across different treatment centers.

Keywords: A.I., Prostate Cancer, Dose Prediction

2738

Digital Poster Abdominal Compression vs Non-Abdominal Compression Planning CT for Cardiac Stereotactic Ablative Radiotherapy (cSABR) Caroline A Sisodia 1 , Shahreen Ahmad 2 , George Ntentas 1 , Marina Khan 3 , Michelle Stenson 1 1 Radiotherapy Physics, Guys & St Thomas NHS Trust, London, United Kingdom. 2 Oncology, Guys & St Thomas NHS Trust, London, United Kingdom. 3 Radiotherapy, Guys & St Thomas NHS Trust, London, United Kingdom Purpose/Objective: Optimal dosimetry for cSABR treatment can be limited by proximity of the myocardial target to dose-limiting structures, particularly the stomach. Motion management techniques are employed to reduce the PTV volume, but may impact the position of the stomach relative to the target. This study presents a comparative analysis of PTV size and stomach overlap for two motion management techniques utilised in the planning and treatment of cSABR: Abdominal Compression (AC) and Non-Abdominal Compression (NAC). Material/Methods: Ten patients underwent dual contrast enhanced respiratory-gated scans under both AC and NAC conditions using a GE Discovery 590RT CT scanner. Compression was provided by means of a Body Pro-Lock ONE Respiratory